کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
727382 1461538 2014 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An adaptive moving total least squares method for curve fitting
ترجمه فارسی عنوان
یک روش حداقل مربعات متحرک برای تنظیم منحنی
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
چکیده انگلیسی


• An Adaptive Moving Total Least Squares (AMTLS) method is presented.
• The direction of local approximants is considered in AMTLS method.
• AMTLS method integrates MLS method and MTLS method.
• Experiments confirm the validity of AMTLS method.

The moving least squares (MLS) method and the moving total least squares (MTLS) method have been developed to deal with the measured data contaminated with random error. The local approximants of MLS method only take into account the error of dependent variable, whereas MTLS method considers the errors of all the variables, which determines the local approximants in the sense of the total least squares. MTLS method is more reasonable than MLS method for dealing with errors-in-variables (EIV) model. But because of the weight function with compact support, it is complicated to choose fitting method for the best performance. This paper presents an Adaptive Moving Total Least Squares (AMTLS) method for EIV model. In AMTLS method, a parameter λ associated with the direction of local approximants is introduced. MLS method and MTLS method can be considered as special cases of AMTLS method. Curve fitting examples are given to prove the better performance of AMTLS method than MLS method and MTLS method.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Measurement - Volume 49, March 2014, Pages 107–112
نویسندگان
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